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Directrices para los protocolos de ensayos clínicos de intervenciones con inteligencia artificial: la extensión SPIRIT-AI / Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension / Diretrizes para protocolos de ensaios clínicos com intervenções que utilizam inteligência artificial: a extensão SPIRIT-AI
Cruz Rivera, Samantha; Liu, Xiaoxuan; Chan, An-Wen; Denniston, Alastair K.; Calvert, Melanie J.; Denniston, Alastair K.; Chan, An-Wen; Darzi, Ara; Holmes, Christopher; Yau, Christopher; Moher, David; Ashrafian, Hutan; Deeks, Jonathan J.; Ferrante di Ruffano, Lavinia; Faes, Livia; Calvert, Melanie J.; Keane, Pearse A.; Cruz Rivera, Samantha; Vollmer, Sebastian J.; Liu, Xiaoxuan; Lee, Aaron Y.; Jonas, Adrian; Esteva, Andre; Beam, Andrew L.; Chan, An-Wen; Panico, Maria Beatrice; Lee, Cecilia S.; Haug, Charlotte; Kelly, Christophe J.; Yau, Christopher; Mulrow, Cynthia; Espinoza, Cyrus; Fletcher, John; Moher, David; Paltoo, Dina; Manna, Elaine; Price, Gary; Collins, Gary S.; Harvey, Hugh; Matcham, James; Monteiro, Joao; Khair ElZarrad, M.; Ferrante di Ruffano, Lavinia; Oakden-Rayner, Luke; Calvert, Melanie J.; McCradden, Melissa; Keane, Pearse A.; Savage, Richard; Golub, Robert; Sarkar, Rupa; Rowley, Samuel; Grupo de Trabajo SPIRIT-AI y CONSORT-AI; Grupo Directivo SPIRIT-AI y CONSORT-AI; Grupo de Consenso SPIRIT-AI y CONSORT-AI.
Afiliação
  • Cruz Rivera, Samantha; Centre for Patient Reported Outcomes Research. Institute of Applied Health Research. University of Birmingham. Birmingham. GB
  • Liu, Xiaoxuan; Birmingham Health Partners Centre for Regulatory Science and Innovation. University of Birmingham. Birmingham. GB
  • Chan, An-Wen; Department of Medicine, Womens College Research Institute. Womens College Hospital. University of Toronto. Ontario. CA
  • Denniston, Alastair K.; Centre for Patient Reported Outcomes Research. Institute of Applied Health Research. University of Birmingham. Birmingham. GB
  • Calvert, Melanie J.; Centre for Patient Reported Outcomes Research. Institute of Applied Health Research. University of Birmingham. Birmingham. GB
  • Denniston, Alastair K.; Centre for Patient Reported Outcomes Research. Institute of Applied Health Research. University of Birmingham. Birmingham. GB
  • Chan, An-Wen; Department of Medicine, Womens College Research Institute. Womens College Hospital. University of Toronto. Ontario. CA
  • Darzi, Ara; Patient Safety Translational Research Centre. Imperial College London. Londres. GB
  • Holmes, Christopher; Alan Turing Institute. Londres. GB
  • Yau, Christopher; Alan Turing Institute. Londres. GB
  • Moher, David; Centre for Journalology. Clinical Epidemiology Program. Ottawa Hospital Research Institute. Ottawa. CA
  • Ashrafian, Hutan; Patient Safety Translational Research Centre. Imperial College London. Londres. GB
  • Deeks, Jonathan J.; Institute of Applied Health Research. University of Birmingham. Birmingham. GB
  • Ferrante di Ruffano, Lavinia; Institute of Applied Health Research. University of Birmingham. Birmingham. GB
  • Faes, Livia; Department of Ophthalmology. Cantonal Hospital Lucerne. Lucerna. CH
  • Calvert, Melanie J.; Centre for Patient Reported Outcomes Research. Institute of Applied Health Research. University of Birmingham. Birmingham. GB
  • Keane, Pearse A.; Centre for Patient Reported Outcomes Research. Institute of Applied Health Research. University of Birmingham. Birmingham. GB
  • Cruz Rivera, Samantha; Centre for Patient Reported Outcomes Research. Institute of Applied Health Research. University of Birmingham. Birmingham. GB
  • Vollmer, Sebastian J.; Alan Turing Institute. Londres. GB
  • Liu, Xiaoxuan; Birmingham Health Partners Centre for Regulatory Science and Innovation. University of Birmingham. Birmingham. GB
  • Lee, Aaron Y.; Department of Ophthalmology. University of Washington. Seattle. US
  • Jonas, Adrian; The National Institute for Health and Care Excellence. Londres. GB
  • Esteva, Andre; Salesforce Research. San Francisco. US
  • Beam, Andrew L.; Harvard T.H. Chan School of Public Health. Boston. US
  • Chan, An-Wen; Department of Medicine, Womens College Research Institute. Womens College Hospital. University of Toronto. Ontario. CA
  • Panico, Maria Beatrice; Medicines and Healthcare products Regulatory Agency. Londres. GB
  • Lee, Cecilia S.; Department of Ophthalmology. University of Washington. Seattle. US
  • Haug, Charlotte; New England Journal of Medicine. Waltham. US
  • Kelly, Christophe J.; Google Health. Londres. GB
  • Yau, Christopher; Alan Turing Institute. Londres. GB
  • Mulrow, Cynthia; Annals of Internal Medicine. Filadelfia. US
  • Espinoza, Cyrus; Patient Partner. Birmingham. GB
  • Fletcher, John; British Medical Journal. Londres. GB
  • Moher, David; Centre for Journalology. Clinical Epidemiology Program. Ottawa Hospital Research Institute. Ottawa. CA
  • Paltoo, Dina; National Institutes of Health. Bethesda. US
  • Manna, Elaine; Patient Partner. Londres. GB
  • Price, Gary; Patient Partner, Centre for Patient Reported Outcome Research. Institute of Applied Health Research. University of Birmingham. Birmingham. GB
  • Collins, Gary S.; Centre for Statistics in Medicine. University of Oxford. Oxford. GB
  • Harvey, Hugh; Hardian Health. Londres. GB
  • Matcham, James; AstraZeneca. Cambridge. GB
  • Monteiro, Joao; Nature Research. Nueva York. US
  • Khair ElZarrad, M.; Food and Drug Administration. Silver Spring. US
  • Ferrante di Ruffano, Lavinia; Institute of Applied Health Research. University of Birmingham. Birmingham. GB
  • Oakden-Rayner, Luke; Australian Institute for Machine Learning. North Terrace, Adelaida. AU
  • Calvert, Melanie J.; Centre for Patient Reported Outcomes Research. Institute of Applied Health Research. University of Birmingham. Birmingham. GB
  • McCradden, Melissa; The Hospital for Sick Children. Toronto. CA
  • Keane, Pearse A.; Centre for Patient Reported Outcomes Research. Institute of Applied Health Research. University of Birmingham. Birmingham. GB
  • Savage, Richard; PinPoint Data Science. Leeds. GB
  • Golub, Robert; Journal of the American Medical Association. Chicago. US
  • Sarkar, Rupa; The Lancet Group. Londres. GB
  • Rowley, Samuel; Medical Research Council. Londres. GB
Rev. panam. salud pública ; 48: e12, 2024. tab, graf
Article em Es | LILACS-Express | LILACS | ID: biblio-1536674
Biblioteca responsável: BR1.1
RESUMEN
resumen está disponible en el texto completo
ABSTRACT
ABSTRACT The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by providing evidence-based recommendations for the minimum set of items to be addressed. This guidance has been instrumental in promoting transparent evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate their impact on health outcomes. The SPIRIT-AI (Standard Protocol Items Recommendations for Interventional Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trial protocols evaluating interventions with an AI component. It was developed in parallel with its companion statement for trial reports CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 26 candidate items, which were consulted upon by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The SPIRIT-AI extension includes 15 new items that were considered sufficiently important for clinical trial protocols of AI interventions. These new items should be routinely reported in addition to the core SPIRIT 2013 items. SPIRIT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention will be integrated, considerations for the handling of input and output data, the human-AI interaction and analysis of error cases. SPIRIT-AI will help promote transparency and completeness for clinical trial protocols for AI interventions. Its use will assist editors and peer reviewers, as well as the general readership, to understand, interpret and critically appraise the design and risk of bias for a planned clinical trial.
RESUMO
RESUMO A declaração SPIRIT 2013 tem como objetivo melhorar a integralidade dos relatórios dos protocolos de ensaios clínicos, fornecendo recomendações baseadas em evidências para o conjunto mínimo de itens que devem ser abordados. Essas orientações têm sido fundamentais para promover uma avaliação transparente de novas intervenções. Recentemente, tem-se reconhecido cada vez mais que intervenções que incluem inteligência artificial (IA) precisam ser submetidas a uma avaliação rigorosa e prospectiva para demonstrar seus impactos sobre os resultados de saúde. A extensão SPIRIT-AI (Standard Protocol Items Recommendations for Interventional Trials - Artificial Intelligence) é uma nova diretriz de relatório para protocolos de ensaios clínicos que avaliam intervenções com um componente de IA. Essa diretriz foi desenvolvida em paralelo à sua declaração complementar para relatórios de ensaios clínicos, CONSORT-AI (Consolidated Standards of Reporting Trials - Artificial Intelligence). Ambas as diretrizes foram desenvolvidas por meio de um processo de consenso em etapas que incluiu revisão da literatura e consultas a especialistas para gerar 26 itens candidatos. Foram feitas consultas sobre esses itens a um grupo internacional composto por 103 interessados diretos, que participaram de uma pesquisa Delphi em duas etapas. Chegou-se a um acordo sobre os itens em uma reunião de consenso que incluiu 31 interessados diretos, e os itens foram refinados por meio de uma lista de verificação piloto que envolveu 34 participantes. A extensão SPIRIT-AI inclui 15 itens novos que foram considerados suficientemente importantes para os protocolos de ensaios clínicos com intervenções que utilizam IA. Esses itens novos devem constar dos relatórios de rotina, juntamente com os itens básicos da SPIRIT 2013. A SPIRIT-AI preconiza que os pesquisadores descrevam claramente a intervenção de IA, incluindo instruções e as habilidades necessárias para seu uso, o contexto no qual a intervenção de IA será integrada, considerações sobre o manuseio dos dados de entrada e saída, a interação humano-IA e a análise de casos de erro. A SPIRIT-AI ajudará a promover a transparência e a integralidade nos protocolos de ensaios clínicos com intervenções que utilizam IA. Seu uso ajudará editores e revisores, bem como leitores em geral, a entender, interpretar e avaliar criticamente o delineamento e o risco de viés de um futuro estudo clínico.

Texto completo: 1 Base de dados: LILACS Idioma: Es Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: LILACS Idioma: Es Ano de publicação: 2024 Tipo de documento: Article